class_docstr: Feature metadata contains information about features that are not directly apparent in the raw data itself.
  This enables feature generators to properly process features, and allows downstream models to properly handle features during training and inference.
  
  Parameters
  ----------
  type_map_raw : Dict[str, str]
      Dictionary of feature names to raw types.
      The values can be anything, but it is generally recommended they be one of:
          ['int', 'float', 'object', 'category', 'datetime']
  type_group_map_special : Dict[str, List[str]], optional
      Dictionary of special types to lists of feature names.
      The keys can be anything, but it is generally recommended they be one of:
          ['binned', 'datetime_as_int', 'datetime_as_object', 'text', 'text_as_category', 'text_special', 'text_ngram', 'image_path', 'stack']
      For descriptions of each special feature-type, see: `autogluon.common.features.types`
      Feature names that appear in the value lists must also be keys in type_map_raw.
      Feature names are not required to have special types.
      Only one of type_group_map_special and type_map_special can be specified.
  type_map_special : Dict[str, List[str]], optional
      Dictionary of feature names to lists of special types.
      This is an alternative representation of the special types.
      Only one of type_group_map_special and type_map_special can be specified.
code: def _remove_features_from_type_map(d, features):
      for feature in features:
          if feature in d:
              d.pop(feature)
  
imports: import copy
  import logging
  from collections import defaultdict
  from typing import Any, Dict, List, Set, Tuple, Union
  import pandas
  from .infer_types import get_type_group_map_special, get_type_map_raw
label_desc: Use image node_id 13 for calling the FeatureMetadata obj's underlying member method code with example usage: obj._remove_features_from_type_map(d, features) without return types